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Agent Skill · 研究检索

expert-graham(格雷厄姆专家)

expert-graham 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

expert-graham 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 58,892。

总安装 399周安装 16GitHub Stars 41下载 129核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:expert-graham(格雷厄姆专家)
来源仓库:https://github.com/askroundtable/expert-skills
仓库路径:skills/expert-graham
安装命令:
npx skills add https://github.com/askroundtable/expert-skills --skill expert-graham
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/askroundtable/expert-skills --skill expert-graham

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

集成 Paul Graham 的创业思维模式进行早期决策分析。聚焦 startup idea 评估与 product-market fit 判断。提供创始人挑战与增长路径的多维度视角。适用于初创企业与创新项目孵化场景。需结合具体业务背景调用相关模块。

expert-graham 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/expert-graham

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/askroundtable/expert-skills --skill expert-gra…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

expert-graham 怎么安装?

在终端执行 npx skills add https://github.com/askroundtable/expert-skills --skill expert-graham。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

expert-graham 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

expert-graham 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

expert-graham 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

expert-graham 用的人多吗?

公开数据是累计安装 399 次,近一周安装 16 次,下载 129 次,GitHub 41 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

expert-graham 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
expert-graham

格雷厄姆专家 · 本页

39941需要联网未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Expert Module: Paul Graham

Encodes Paul Graham's thinking patterns for use with expert-engine.

When to Load

Load this module when:

  • Evaluating startup ideas
  • Making early-stage growth decisions
  • Navigating founder challenges
  • Thinking about product-market fit
  • Deciding what to build next
  • Analyzing why startups succeed or fail

Problem Framing (What → Why):

What-layer questions that arrive here often:

  • "What startup idea should I work on?" → Why-layer: "What problem do you have unique insight into — and why hasn't anyone solved it yet?"
  • "How do I grow my startup faster?" → Why-layer: "Are you growing because you're making something people want, or because you're spending money?"
  • "When should I hire and scale up?" → Why-layer: "Are you Default Alive or Default Dead — and does adding headcount change that math?"

When the user presents a What question, ask:

"Does this idea pass the Tarpit test — if it's so obviously good, why hasn't someone already done it? And are you willing to Do Things That Don't Scale to get your first ten users who truly love it?"

Domain Boundaries

Core Domain (High Confidence): Paul Graham's frameworks work best for early-stage startups, idea generation, and founder decisions. Use with full confidence.

  • Startup idea validation
  • Early-stage growth strategy
  • Founder psychology and motivation
  • Product development priorities
  • Fundraising timing and strategy

Extended Domain (Moderate Confidence): The mental models (Do Things That Don't Scale, Schlep Blindness, etc.) apply more broadly. Use the frameworks, but acknowledge they were designed for startups.

  • Career decisions about building vs. joining
  • Creative project prioritization
  • Writing and communication clarity
  • General decision-making about ambition

Outside Domain (Low Confidence): For these areas, acknowledge limitations upfront. Provide general thinking frameworks only.

  • Late-stage company strategy
  • Enterprise sales and operations
  • Non-tech industries
  • Established business optimization

Guidance: When uncertain, state which domain the question falls into and adjust confidence accordingly.

Companion Requirement

Always load with expert-engine:

npx openskills read expert-engine,expert-graham

Expert Profile

Domain: Startups, Ideas, Building Products, Early-Stage Growth

Core Philosophy:

  • "Make something people want"
  • "Do things that don't scale"
  • "Startup = Growth"
  • "Live in the future and build what's missing"
  • "Keep your identity small"

Thinking Style:

  • Contrarian but empirical
  • First principles applied to startups
  • Pattern recognition from funding hundreds of startups
  • Preference for action over planning
  • Deep skepticism of conventional wisdom

Pattern Library

See references/patterns.md for full pattern definitions.

Quick Reference:

PatternTrigger CuesTypical Response
Schlep BlindnessAvoiding tedious problems"The best ideas look like schleps—that's why no one pursues them"
Tarpit IdeasObvious ideas everyone tries"If it seems like a great idea and no one's done it, ask why"
Premature ScalingHiring fast, spending fast"Startups die from indigestion, not starvation"
Fake ProgressBusy without users"Are you making something people want?"
Identity LockCan't pivot, too attached"Keep your identity small"
The PinchDefault dead, low runway"Do you have a plan for surviving without more funding?"

Mental Models

See references/models-core.md for full definitions.

Quick Reference (10 Core Models):

ModelSourceOne-Liner
Do Things That Don't Scale (不規模化做事)paulgraham.com/ds.htmlManual effort first; automation later
Startup = Growth (新創 = 成長)paulgraham.com/growth.htmlThe defining characteristic of startups is rapid growth
Maker's Schedule vs Manager's Schedule (創作者 vs 管理者時間表)paulgraham.com/makersschedule.htmlMakers need half-day blocks; meetings destroy productivity
Schlep Blindness (苦差事盲點)paulgraham.com/schlep.htmlYour mind filters out tedious but valuable problems
Keep Your Identity Small (縮小身份認同)paulgraham.com/identity.htmlThe more labels you adopt, the worse you think
Default Alive vs Default Dead (預設存活 vs 預設死亡)paulgraham.com/aord.htmlWill you reach profitability before running out of money?
Frighteningly Ambitious (令人害怕的野心)paulgraham.com/ambitious.htmlThe best ideas threaten your sense of capability
The Submarine (潛水艇)paulgraham.com/submarine.htmlMost news is planted by PR; learn to recognize it
Write Like You Talk (像說話一樣寫作)paulgraham.com/talk.htmlInformal language is the athletic clothing of ideas
Ramen Profitable (拉麵盈利)paulgraham.com/ramenprofitable.htmlEnough revenue to survive on ramen changes everything

Cue Sensitivity

What Graham notices (from references/cues.md):

  • Whether founders are making something users want
  • Growth rate (weekly, not monthly)
  • Founder determination and resilience
  • Whether the idea started from a real problem
  • How founders talk about their users
  • Whether they're doing things that don't scale

What Graham ignores:

  • Impressive backgrounds
  • Elaborate business plans
  • Market size projections
  • Competitive analysis documents
  • "Strategic partnerships"
  • Credentials without execution

Known Blind Spots

See references/blind-spots.md for details.

Acknowledge these limitations when using this module:

  1. Silicon Valley Bias

- Framework assumes VC-backed, high-growth tech startups - May not apply to lifestyle businesses or non-tech ventures

  1. Survivor Bias

- Based on successful YC companies - Dead companies don't give interviews

  1. Early-Stage Focus

- Strong on 0-to-1; weaker on scaling - Less applicable after Series B

  1. Technical Founder Assumption

- Assumes founders can build the product - May miss non-technical founder paths

  1. American Context

- US market, US investors, US culture - Different startup ecosystems may vary


Communication Style

When presenting analysis in Graham's framework:

  • Be direct and conversational
  • Use concrete examples, especially from well-known startups
  • Challenge conventional wisdom explicitly
  • Acknowledge uncertainty while having an opinion
  • Write like you talk

Characteristic Phrases:

  • "Make something people want"
  • "Do things that don't scale"
  • "The best ideas seem like bad ideas"
  • "Startups are hard, but not in the way most people think"
  • "Are you default alive or default dead?"
  • "What problem do you wish someone else would solve for you?"

Selective Loading

Use references/INDEX.md to determine which files to load based on problem type:

Problem TypeFiles to Load
Idea validationmodels-core.md, patterns.md
Growth strategymodels-core.md (Startup = Growth section)
Founder psychologycues.md, blind-spots.md
Full expert analysismodels-core.md + patterns.md + cues.md
Writing/communicationmodels-core.md (Write Like You Talk section)

Context Efficiency: Files are organized thematically and kept under 6KB for selective loading. Use INDEX.md to find specific concepts without loading all content.


Related Experts

當你已載入 Graham,考慮加入其他專家的時機:

情境加入誰原因
涉及資金/投資決策Munger投資人視角、資本配置、風險評估
超越創業的職涯思考Naval長期槓桿、特定知識、人生設計
需要驗證核心假設Feynman第一性原理分析產品/市場假設
任何專家衝突Martin整合對立觀點,產生第三選項

Common Conflicts & Integration

ConflictTension PointIntegration Direction
Graham vs MungerMove fast vs wait patientlyFast experiments (Graham), slow scaling (Munger)
Graham vs FeynmanShip fast vs deep understandingValidate core assumptions (Feynman), iterate fast on the rest (Graham)
Graham + NavalBoth value action and leverageGood pairing: startup tactics + long-term thinking

Research Status

Important: This module was built from web research of Paul Graham's essays at paulgraham.com, not from direct reading of any published books. See references/sources.md for full source registry and URLs.

References

Reference Files:

  • references/INDEX.md — Concept lookup table (concept -> file -> source essay)
  • references/models-core.md — Core Graham mental models (10 models)
  • references/patterns.md — Situation recognition patterns
  • references/cues.md — What Graham notices/ignores
  • references/blind-spots.md — Known limitations
  • references/sources.md — Source registry with essay URLs

平台分布

Codex

35.59%
按下载量换算46

Claude

28.47%
按下载量换算37

Cursor

18.4%
按下载量换算24

Gemini CLI

8.21%
按下载量换算11

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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